During the Covid-19 pandemic, public sector organizations have rapidly increased their use of social media platforms to directly communicate with citizens regarding various aspects of the crisis. Given the critical importance of epidemiological data during this period, this study conducts a quantitative analysis of the official Facebook channels of the 20 Italian regions in the initial emergency phase to explore the role of data communication. It employs computational methods for automated classification of the prevailing types of data communication on Facebook posts and a random-intercept negative binomial model to analyze their different impact on engagement. The findings reveal that the most common types of posts incorporate data within the message, either alone or accompanied by a link to the official website. Infographics are also commonly used. Furthermore, the most comprehensive posts, featuring data, a link to a website, and an infographic, had the highest positive impact on engagement. Overall, the study highlights a significant diversity in the way of communicating epidemiologic data, potentially leading to disparities among Italian citizens in receiving information from institutions about the spread of the virus. This poses substantial challenges for public health communication directed at citizens and the relationships between the national and local levels.

Challenges in Communicating Public Health Data. An Analysis of Italian Regions' Social Media Use During the Covid-19 Pandemic on Facebook

Alessandro Lovari;
2024-01-01

Abstract

During the Covid-19 pandemic, public sector organizations have rapidly increased their use of social media platforms to directly communicate with citizens regarding various aspects of the crisis. Given the critical importance of epidemiological data during this period, this study conducts a quantitative analysis of the official Facebook channels of the 20 Italian regions in the initial emergency phase to explore the role of data communication. It employs computational methods for automated classification of the prevailing types of data communication on Facebook posts and a random-intercept negative binomial model to analyze their different impact on engagement. The findings reveal that the most common types of posts incorporate data within the message, either alone or accompanied by a link to the official website. Infographics are also commonly used. Furthermore, the most comprehensive posts, featuring data, a link to a website, and an infographic, had the highest positive impact on engagement. Overall, the study highlights a significant diversity in the way of communicating epidemiologic data, potentially leading to disparities among Italian citizens in receiving information from institutions about the spread of the virus. This poses substantial challenges for public health communication directed at citizens and the relationships between the national and local levels.
2024
Health data communication; Public sector communication; Social media; Covid-19 pandemic; Engagement; Italy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/394043
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